kpca

 
  • 核主成分分析

KPCA的用法和样例:

例句

  1. A novel modeling method integrated KPCA with RVM was proposed.
    摘要提出了一种核主元分析(KPCA)和关联向量机(RVM)相结合的组合建模方法。
  2. So KPCA can extract the feature set more suitable in categorization than classical conventional PCA.
    核主成分分析与传统主成分分析相比,可以得到更好的适合分类的特征。
  3. KPCA extracting principal component with nonlinear method is an improved conventional PCA.
    摘要核主成分分析方法是主成分分析的改进算法,其采用非线性方法提取主成分。
  4. Based on ORL face database, recognizes correlation coefficients of principal component extracted by KPCA.
    基于ORL人脸库,识别核主成分分析提取出的主成分的相关性系数。
  5. A novel approach of fault identification of KPCA is presented, which is called the contribution plots method.
    摘要提出一种新的针对KPCA模型的故障识别方法-贡献率图法。
  6. Conclusion Integrating KPCA algorithm with ANN for pattern recognition of quality control of Radix Paeoniae Alba has been proved to be available.
    结论非线性特征提取KPCA法与人工神经网络结合适用于白芍整体质量分析。

KPCA的相关资料:

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